The role of analysis error in the convergence of reanalysis production streams in MERRA-2
Due to production time constraints, most reanalyses are produced in multiple parallel streams instead of a single continuous one. These streams cover separate segments of the reanalysis time period with short overlaps to allow reconstruction of the official record. A fundamental assumption justifyin...
Gespeichert in:
Veröffentlicht in: | Monthly weather review 2021-04, Vol.149 (4), p.1041-1054 |
---|---|
Hauptverfasser: | , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 1054 |
---|---|
container_issue | 4 |
container_start_page | 1041 |
container_title | Monthly weather review |
container_volume | 149 |
creator | Akkraoui, Amal El Carvalho, David Errico, Ronald M. Prive, Nikki C Bosilovich, Michael G. |
description | Due to production time constraints, most reanalyses are produced in multiple parallel streams instead of a single continuous one. These streams cover separate segments of the reanalysis time period with short overlaps to allow reconstruction of the official record. A fundamental assumption justifying this approach is that the streams will be assimilating the same observations during the periods where they overlap, and so will eventually converge to a similar atmospheric state, making discontinuities at stream junctions negligible. This assumption is revisited in this work by examining the impact of analysis error on the differences between MERRA-2 overlapping streams in three historical periods. Comparison results are shown in terms of standard deviations of stream differences as well as the spectral decomposition of the variance of their differences. Residual differences were found at the end of each year of overlap, with larger values observed in the earlier segments of the presatellite era. By drawing parallels with analysis error statistics estimated from the GMAO OSSE system, these differences are shown to reflect the varying constraint of data with the varying observing network, and to further carry the imprint of errors that the data assimilation process is not able to mitigate. As such, they are unlikely to be reduced by longer spinup periods. The ability of data assimilation to ensure continuity in the parallel streams is put into question when the observing system coverage is inadequate or simply when the data assimilation system as a whole is suboptimal. |
doi_str_mv | 10.1175/MWR-D-20-0256.1 |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2511229463</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2511229463</sourcerecordid><originalsourceid>FETCH-LOGICAL-c244t-a9d0595031665fc5c4569765734ec4453d0564f97a5621e5871b4e6a466d262e3</originalsourceid><addsrcrecordid>eNo9kM1LAzEQxYMoWKtnLx4WPKedZDOz7rG09QNahFIRTyGmWd3SbmqyFfrfm7XiaZh5vzc8HmPXAgZCFDicvy74hEvgIJEG4oT1BHabKvNT1gOQBQdS6pxdxLgGACIle-xt-emy4Dcu81VmGrM5xDpmLgQfsrrJ2qRa33y78OEa-wsF94_tgl_tbVv7Jottum9j55lPF4sRl5fsrDKb6K7-Zp-93E-X40c-e354Go9m3EqlWm7KFWCJkAsirCxahVQWhEWunFUK8ySTqsrCIEnh8K4Q78qRUUQrSdLlfXZ7_JvSfO1dbPXa70OKGLVEIaQsFeWJGh4pG3yMwVV6F-qtCQctQHf96dSfnmgJuutPi-S4OToaE41u2pD-gQQESBkw_wH-IWmm</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2511229463</pqid></control><display><type>article</type><title>The role of analysis error in the convergence of reanalysis production streams in MERRA-2</title><source>American Meteorological Society</source><source>NASA Technical Reports Server</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><source>Alma/SFX Local Collection</source><creator>Akkraoui, Amal El ; Carvalho, David ; Errico, Ronald M. ; Prive, Nikki C ; Bosilovich, Michael G.</creator><creatorcontrib>Akkraoui, Amal El ; Carvalho, David ; Errico, Ronald M. ; Prive, Nikki C ; Bosilovich, Michael G.</creatorcontrib><description>Due to production time constraints, most reanalyses are produced in multiple parallel streams instead of a single continuous one. These streams cover separate segments of the reanalysis time period with short overlaps to allow reconstruction of the official record. A fundamental assumption justifying this approach is that the streams will be assimilating the same observations during the periods where they overlap, and so will eventually converge to a similar atmospheric state, making discontinuities at stream junctions negligible. This assumption is revisited in this work by examining the impact of analysis error on the differences between MERRA-2 overlapping streams in three historical periods. Comparison results are shown in terms of standard deviations of stream differences as well as the spectral decomposition of the variance of their differences. Residual differences were found at the end of each year of overlap, with larger values observed in the earlier segments of the presatellite era. By drawing parallels with analysis error statistics estimated from the GMAO OSSE system, these differences are shown to reflect the varying constraint of data with the varying observing network, and to further carry the imprint of errors that the data assimilation process is not able to mitigate. As such, they are unlikely to be reduced by longer spinup periods. The ability of data assimilation to ensure continuity in the parallel streams is put into question when the observing system coverage is inadequate or simply when the data assimilation system as a whole is suboptimal.</description><identifier>ISSN: 0027-0644</identifier><identifier>EISSN: 1520-0493</identifier><identifier>DOI: 10.1175/MWR-D-20-0256.1</identifier><language>eng</language><publisher>Goddard Space Flight Center: American Meteorological Society</publisher><subject>Convergence ; Data ; Data assimilation ; Data collection ; Error analysis ; Impact analysis ; Meteorology And Climatology ; Numerical Analysis ; Rivers ; Segments ; Statistical analysis ; Statistical methods ; Streams</subject><ispartof>Monthly weather review, 2021-04, Vol.149 (4), p.1041-1054</ispartof><rights>Copyright Determination: GOV_PERMITTED</rights><rights>Copyright American Meteorological Society Apr 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,796,3668,27903,27904</link.rule.ids></links><search><creatorcontrib>Akkraoui, Amal El</creatorcontrib><creatorcontrib>Carvalho, David</creatorcontrib><creatorcontrib>Errico, Ronald M.</creatorcontrib><creatorcontrib>Prive, Nikki C</creatorcontrib><creatorcontrib>Bosilovich, Michael G.</creatorcontrib><title>The role of analysis error in the convergence of reanalysis production streams in MERRA-2</title><title>Monthly weather review</title><description>Due to production time constraints, most reanalyses are produced in multiple parallel streams instead of a single continuous one. These streams cover separate segments of the reanalysis time period with short overlaps to allow reconstruction of the official record. A fundamental assumption justifying this approach is that the streams will be assimilating the same observations during the periods where they overlap, and so will eventually converge to a similar atmospheric state, making discontinuities at stream junctions negligible. This assumption is revisited in this work by examining the impact of analysis error on the differences between MERRA-2 overlapping streams in three historical periods. Comparison results are shown in terms of standard deviations of stream differences as well as the spectral decomposition of the variance of their differences. Residual differences were found at the end of each year of overlap, with larger values observed in the earlier segments of the presatellite era. By drawing parallels with analysis error statistics estimated from the GMAO OSSE system, these differences are shown to reflect the varying constraint of data with the varying observing network, and to further carry the imprint of errors that the data assimilation process is not able to mitigate. As such, they are unlikely to be reduced by longer spinup periods. The ability of data assimilation to ensure continuity in the parallel streams is put into question when the observing system coverage is inadequate or simply when the data assimilation system as a whole is suboptimal.</description><subject>Convergence</subject><subject>Data</subject><subject>Data assimilation</subject><subject>Data collection</subject><subject>Error analysis</subject><subject>Impact analysis</subject><subject>Meteorology And Climatology</subject><subject>Numerical Analysis</subject><subject>Rivers</subject><subject>Segments</subject><subject>Statistical analysis</subject><subject>Statistical methods</subject><subject>Streams</subject><issn>0027-0644</issn><issn>1520-0493</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>CYI</sourceid><recordid>eNo9kM1LAzEQxYMoWKtnLx4WPKedZDOz7rG09QNahFIRTyGmWd3SbmqyFfrfm7XiaZh5vzc8HmPXAgZCFDicvy74hEvgIJEG4oT1BHabKvNT1gOQBQdS6pxdxLgGACIle-xt-emy4Dcu81VmGrM5xDpmLgQfsrrJ2qRa33y78OEa-wsF94_tgl_tbVv7Jottum9j55lPF4sRl5fsrDKb6K7-Zp-93E-X40c-e354Go9m3EqlWm7KFWCJkAsirCxahVQWhEWunFUK8ySTqsrCIEnh8K4Q78qRUUQrSdLlfXZ7_JvSfO1dbPXa70OKGLVEIaQsFeWJGh4pG3yMwVV6F-qtCQctQHf96dSfnmgJuutPi-S4OToaE41u2pD-gQQESBkw_wH-IWmm</recordid><startdate>20210401</startdate><enddate>20210401</enddate><creator>Akkraoui, Amal El</creator><creator>Carvalho, David</creator><creator>Errico, Ronald M.</creator><creator>Prive, Nikki C</creator><creator>Bosilovich, Michael G.</creator><general>American Meteorological Society</general><scope>CYE</scope><scope>CYI</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QH</scope><scope>7TG</scope><scope>7TN</scope><scope>7UA</scope><scope>8FD</scope><scope>C1K</scope><scope>F1W</scope><scope>H8D</scope><scope>H96</scope><scope>KL.</scope><scope>L.G</scope><scope>L7M</scope></search><sort><creationdate>20210401</creationdate><title>The role of analysis error in the convergence of reanalysis production streams in MERRA-2</title><author>Akkraoui, Amal El ; Carvalho, David ; Errico, Ronald M. ; Prive, Nikki C ; Bosilovich, Michael G.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c244t-a9d0595031665fc5c4569765734ec4453d0564f97a5621e5871b4e6a466d262e3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Convergence</topic><topic>Data</topic><topic>Data assimilation</topic><topic>Data collection</topic><topic>Error analysis</topic><topic>Impact analysis</topic><topic>Meteorology And Climatology</topic><topic>Numerical Analysis</topic><topic>Rivers</topic><topic>Segments</topic><topic>Statistical analysis</topic><topic>Statistical methods</topic><topic>Streams</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Akkraoui, Amal El</creatorcontrib><creatorcontrib>Carvalho, David</creatorcontrib><creatorcontrib>Errico, Ronald M.</creatorcontrib><creatorcontrib>Prive, Nikki C</creatorcontrib><creatorcontrib>Bosilovich, Michael G.</creatorcontrib><collection>NASA Scientific and Technical Information</collection><collection>NASA Technical Reports Server</collection><collection>CrossRef</collection><collection>Aqualine</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Oceanic Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aerospace Database</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>Monthly weather review</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Akkraoui, Amal El</au><au>Carvalho, David</au><au>Errico, Ronald M.</au><au>Prive, Nikki C</au><au>Bosilovich, Michael G.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The role of analysis error in the convergence of reanalysis production streams in MERRA-2</atitle><jtitle>Monthly weather review</jtitle><date>2021-04-01</date><risdate>2021</risdate><volume>149</volume><issue>4</issue><spage>1041</spage><epage>1054</epage><pages>1041-1054</pages><issn>0027-0644</issn><eissn>1520-0493</eissn><abstract>Due to production time constraints, most reanalyses are produced in multiple parallel streams instead of a single continuous one. These streams cover separate segments of the reanalysis time period with short overlaps to allow reconstruction of the official record. A fundamental assumption justifying this approach is that the streams will be assimilating the same observations during the periods where they overlap, and so will eventually converge to a similar atmospheric state, making discontinuities at stream junctions negligible. This assumption is revisited in this work by examining the impact of analysis error on the differences between MERRA-2 overlapping streams in three historical periods. Comparison results are shown in terms of standard deviations of stream differences as well as the spectral decomposition of the variance of their differences. Residual differences were found at the end of each year of overlap, with larger values observed in the earlier segments of the presatellite era. By drawing parallels with analysis error statistics estimated from the GMAO OSSE system, these differences are shown to reflect the varying constraint of data with the varying observing network, and to further carry the imprint of errors that the data assimilation process is not able to mitigate. As such, they are unlikely to be reduced by longer spinup periods. The ability of data assimilation to ensure continuity in the parallel streams is put into question when the observing system coverage is inadequate or simply when the data assimilation system as a whole is suboptimal.</abstract><cop>Goddard Space Flight Center</cop><pub>American Meteorological Society</pub><doi>10.1175/MWR-D-20-0256.1</doi><tpages>14</tpages><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 0027-0644 |
ispartof | Monthly weather review, 2021-04, Vol.149 (4), p.1041-1054 |
issn | 0027-0644 1520-0493 |
language | eng |
recordid | cdi_proquest_journals_2511229463 |
source | American Meteorological Society; NASA Technical Reports Server; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; Alma/SFX Local Collection |
subjects | Convergence Data Data assimilation Data collection Error analysis Impact analysis Meteorology And Climatology Numerical Analysis Rivers Segments Statistical analysis Statistical methods Streams |
title | The role of analysis error in the convergence of reanalysis production streams in MERRA-2 |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-28T08%3A36%3A55IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=The%20role%20of%20analysis%20error%20in%20the%20convergence%20of%20reanalysis%20production%20streams%20in%20MERRA-2&rft.jtitle=Monthly%20weather%20review&rft.au=Akkraoui,%20Amal%20El&rft.date=2021-04-01&rft.volume=149&rft.issue=4&rft.spage=1041&rft.epage=1054&rft.pages=1041-1054&rft.issn=0027-0644&rft.eissn=1520-0493&rft_id=info:doi/10.1175/MWR-D-20-0256.1&rft_dat=%3Cproquest_cross%3E2511229463%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2511229463&rft_id=info:pmid/&rfr_iscdi=true |